sync dev to main

This commit is contained in:
Lincoln Stein 2022-11-13 13:47:26 +00:00
commit 23348dcd3f
93 changed files with 11563 additions and 15109 deletions

1
.github/CODEOWNERS vendored
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@ -2,3 +2,4 @@ ldm/invoke/pngwriter.py @CapableWeb
ldm/invoke/server_legacy.py @CapableWeb
scripts/legacy_api.py @CapableWeb
tests/legacy_tests.sh @CapableWeb
installer/ @tildebyte

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@ -17,9 +17,9 @@ jobs:
- aarch64
include:
- arch: x86_64
conda-env-file: environment.yml
conda-env-file: environment-lin-cuda.yml
- arch: aarch64
conda-env-file: environment-linux-aarch64.yml
conda-env-file: environment-lin-aarch64.yml
runs-on: ubuntu-latest
name: ${{ matrix.arch }}
steps:

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@ -22,7 +22,7 @@ jobs:
- macOS-12
include:
- os: ubuntu-latest
environment-file: environment.yml
environment-file: environment-lin-cuda.yml
default-shell: bash -l {0}
- os: macOS-12
environment-file: environment-mac.yml
@ -48,6 +48,9 @@ jobs:
- name: create models.yaml from example
run: cp configs/models.yaml.example configs/models.yaml
- name: create environment.yml
run: cp environments-and-requirements/${{ matrix.environment-file }} environment.yml
- name: Use cached conda packages
id: use-cached-conda-packages
uses: actions/cache@v3
@ -60,7 +63,7 @@ jobs:
uses: conda-incubator/setup-miniconda@v2
with:
activate-environment: ${{ env.CONDA_ENV_NAME }}
environment-file: ${{ matrix.environment-file }}
environment-file: environment.yml
miniconda-version: latest
- name: set test prompt to main branch validation

25
.gitignore vendored
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@ -194,6 +194,10 @@ checkpoints
# Let the frontend manage its own gitignore
!frontend/*
frontend/apt-get
frontend/dist
frontend/sudo
frontend/update
# Scratch folder
.scratch/
@ -201,6 +205,7 @@ checkpoints
gfpgan/
models/ldm/stable-diffusion-v1/*.sha256
# GFPGAN model files
gfpgan/
@ -209,6 +214,24 @@ configs/models.yaml
# weights (will be created by installer)
models/ldm/stable-diffusion-v1/*.ckpt
models/clipseg
models/gfpgan
# ignore initfile
invokeai.init
.invokeai
# ignore environment.yml and requirements.txt
# these are links to the real files in environments-and-requirements
environment.yml
requirements.txt
# source installer files
source_installer/*zip
source_installer/invokeAI
install.bat
install.sh
update.bat
update.sh
# this may be present if the user created a venv
invokeai

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@ -43,33 +43,42 @@ RUN apt-get update \
ARG invokeai_git=invoke-ai/InvokeAI
ARG invokeai_branch=main
ARG project_name=invokeai
RUN git clone -b ${invokeai_branch} https://github.com/${invokeai_git}.git /${project_name} \
&& cp /${project_name}/configs/models.yaml.example /${project_name}/configs/models.yaml \
&& ln -s /data/models/v1-5-pruned-emaonly.ckpt /${project_name}/models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt \
&& ln -s /data/outputs/ /${project_name}/outputs
ARG conda_env_file=environment-lin-cuda.yml
RUN git clone -b ${invokeai_branch} https://github.com/${invokeai_git}.git "/${project_name}" \
&& cp \
"/${project_name}/configs/models.yaml.example" \
"/${project_name}/configs/models.yaml" \
&& ln -sf \
"/${project_name}/environments-and-requirements/${conda_env_file}" \
"/${project_name}/environment.yml" \
&& ln -sf \
/data/models/v1-5-pruned-emaonly.ckpt \
"/${project_name}/models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt" \
&& ln -sf \
/data/outputs/ \
"/${project_name}/outputs"
# set workdir
WORKDIR /${project_name}
WORKDIR "/${project_name}"
# install conda env and preload models
ARG conda_prefix=/opt/conda
ARG conda_env_file=environment.yml
COPY --from=get_miniconda ${conda_prefix} ${conda_prefix}
RUN source ${conda_prefix}/etc/profile.d/conda.sh \
COPY --from=get_miniconda "${conda_prefix}" "${conda_prefix}"
RUN source "${conda_prefix}/etc/profile.d/conda.sh" \
&& conda init bash \
&& source ~/.bashrc \
&& conda env create \
--name ${project_name} \
--file ${conda_env_file} \
--name "${project_name}" \
&& rm -Rf ~/.cache \
&& conda clean -afy \
&& echo "conda activate ${project_name}" >> ~/.bashrc \
&& conda activate ${project_name} \
&& echo "conda activate ${project_name}" >> ~/.bashrc
RUN source ~/.bashrc \
&& python scripts/preload_models.py \
--no-interactive
# Copy entrypoint and set env
ENV CONDA_PREFIX=${conda_prefix}
ENV PROJECT_NAME=${project_name}
ENV CONDA_PREFIX="${conda_prefix}"
ENV PROJECT_NAME="${project_name}"
COPY docker-build/entrypoint.sh /
ENTRYPOINT [ "/entrypoint.sh" ]

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@ -8,7 +8,7 @@ source ./docker-build/env.sh || echo "please run from repository root" || exit 1
invokeai_conda_version=${INVOKEAI_CONDA_VERSION:-py39_4.12.0-${platform/\//-}}
invokeai_conda_prefix=${INVOKEAI_CONDA_PREFIX:-\/opt\/conda}
invokeai_conda_env_file=${INVOKEAI_CONDA_ENV_FILE:-environment.yml}
invokeai_conda_env_file=${INVOKEAI_CONDA_ENV_FILE:-environment-lin-cuda.yml}
invokeai_git=${INVOKEAI_GIT:-invoke-ai/InvokeAI}
invokeai_branch=${INVOKEAI_BRANCH:-main}
huggingface_token=${HUGGINGFACE_TOKEN?}

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@ -19,13 +19,13 @@ tree on a hill with a river, nature photograph, national geographic -I./test-pic
This will take the original image shown here:
<figure markdown>
![](https://user-images.githubusercontent.com/50542132/193946000-c42a96d8-5a74-4f8a-b4c3-5213e6cadcce.png)
![original-image](https://user-images.githubusercontent.com/50542132/193946000-c42a96d8-5a74-4f8a-b4c3-5213e6cadcce.png){ width=320 }
</figure>
and generate a new image based on it as shown here:
<figure markdown>
![](https://user-images.githubusercontent.com/111189/194135515-53d4c060-e994-4016-8121-7c685e281ac9.png)
![generated-image](https://user-images.githubusercontent.com/111189/194135515-53d4c060-e994-4016-8121-7c685e281ac9.png){ width=320 }
</figure>
The `--init_img` (`-I`) option gives the path to the seed picture. `--strength`
@ -45,15 +45,16 @@ Note that the prompt makes a big difference. For example, this slight variation
on the prompt produces a very different image:
<figure markdown>
![](https://user-images.githubusercontent.com/111189/194135220-16b62181-b60c-4248-8989-4834a8fd7fbd.png)
![](https://user-images.githubusercontent.com/111189/194135220-16b62181-b60c-4248-8989-4834a8fd7fbd.png){ width=320 }
<caption markdown>photograph of a tree on a hill with a river</caption>
</figure>
!!! tip
When designing prompts, think about how the images scraped from the internet were captioned. Very few photographs will
be labeled "photograph" or "photorealistic." They will, however, be captioned with the publication, photographer, camera
model, or film settings.
When designing prompts, think about how the images scraped from the internet were
captioned. Very few photographs will be labeled "photograph" or "photorealistic."
They will, however, be captioned with the publication, photographer, camera model,
or film settings.
If the initial image contains transparent regions, then Stable Diffusion will
only draw within the transparent regions, a process called
@ -61,17 +62,17 @@ only draw within the transparent regions, a process called
However, for this to work correctly, the color information underneath the
transparent needs to be preserved, not erased.
!!! warning
!!! warning "**IMPORTANT ISSUE** "
**IMPORTANT ISSUE** `img2img` does not work properly on initial images smaller
than 512x512. Please scale your image to at least 512x512 before using it.
Larger images are not a problem, but may run out of VRAM on your GPU card. To
fix this, use the --fit option, which downscales the initial image to fit within
the box specified by width x height:
`img2img` does not work properly on initial images smaller
than 512x512. Please scale your image to at least 512x512 before using it.
Larger images are not a problem, but may run out of VRAM on your GPU card. To
fix this, use the --fit option, which downscales the initial image to fit within
the box specified by width x height:
```
tree on a hill with a river, national geographic -I./test-pictures/big-sketch.png -H512 -W512 --fit
```
```
tree on a hill with a river, national geographic -I./test-pictures/big-sketch.png -H512 -W512 --fit
```
## How does it actually work, though?
@ -87,7 +88,7 @@ from a prompt. If the step count is 10, then the "latent space" (Stable
Diffusion's internal representation of the image) for the prompt "fire" with
seed `1592514025` develops something like this:
```commandline
```bash
invoke> "fire" -s10 -W384 -H384 -S1592514025
```
@ -133,9 +134,9 @@ Notice how much more fuzzy the starting image is for strength `0.7` compared to
| | strength = 0.7 | strength = 0.4 |
| --------------------------- | ------------------------------------------------------------- | ------------------------------------------------------------- |
| initial image that SD sees | ![](../assets/img2img/000032.step-0.png) | ![](../assets/img2img/000030.step-0.png) |
| initial image that SD sees | ![step-0](../assets/img2img/000032.step-0.png) | ![step-0](../assets/img2img/000030.step-0.png) |
| steps argument to `invoke>` | `-S10` | `-S10` |
| steps actually taken | 7 | 4 |
| steps actually taken | `7` | `4` |
| latent space at each step | ![gravity32](../assets/img2img/000032.steps.gravity.png) | ![gravity30](../assets/img2img/000030.steps.gravity.png) |
| output | ![000032.1592514025](../assets/img2img/000032.1592514025.png) | ![000030.1592514025](../assets/img2img/000030.1592514025.png) |
@ -150,7 +151,7 @@ If you want to try this out yourself, all of these are using a seed of
`1592514025` with a width/height of `384`, step count `10`, the default sampler
(`k_lms`), and the single-word prompt `"fire"`:
```commandline
```bash
invoke> "fire" -s10 -W384 -H384 -S1592514025 -I /tmp/fire-drawing.png --strength 0.7
```
@ -170,7 +171,7 @@ give each generation 20 steps.
Here's strength `0.4` (note step count `50`, which is `20 ÷ 0.4` to make sure SD
does `20` steps from my image):
```commandline
```bash
invoke> "fire" -s50 -W384 -H384 -S1592514025 -I /tmp/fire-drawing.png -f 0.4
```

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@ -126,7 +126,7 @@ A number of caveats:
the border.
4. When using the `inpaint-1.5` model, you may notice subtle changes to the area
within the original image. This is because the model performs an
outside the masked region. This is because the model performs an
encoding/decoding on the image as a whole. This does not occur with the
standard model.

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@ -2,7 +2,7 @@
title: WebUI Hotkey List
---
# **WebUI Hotkey List**
# :material-keyboard: **WebUI Hotkey List**
## General
@ -19,7 +19,7 @@ title: WebUI Hotkey List
| ++ctrl+enter++ | Start processing |
| ++shift+x++ | cancel Processing |
| ++shift+d++ | Toggle Dark Mode |
| ` | Toggle console |
| ++"`"++ | Toggle console |
## Tabs
@ -48,10 +48,10 @@ title: WebUI Hotkey List
| Setting | Hotkey |
| ---------------------------- | --------------------- |
| [ | Decrease brush size |
| ] | Increase brush size |
| alt + [ | Decrease mask opacity |
| alt + ] | Increase mask opacity |
| ++"["++ | Decrease brush size |
| ++"]"++ | Increase brush size |
| ++alt+"["++ | Decrease mask opacity |
| ++alt+"]"++ | Increase mask opacity |
| ++b++ | Select brush |
| ++e++ | Select eraser |
| ++ctrl+z++ | Undo brush stroke |

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@ -94,6 +94,7 @@ installation instructions below.
You wil need one of the following:
- :simple-nvidia: An NVIDIA-based graphics card with 4 GB or more VRAM memory.
- :simple-amd: An AMD-based graphics card with 4 GB or more VRAM memory (Linux only)
- :fontawesome-brands-apple: An Apple computer with an M1 chip.
### :fontawesome-solid-memory: Memory

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@ -4,26 +4,30 @@ title: Docker
# :fontawesome-brands-docker: Docker
## Before you begin
!!! warning "For end users"
- For end users: Install Stable Diffusion locally using the instructions for
your OS.
- For developers: For container-related development tasks or for enabling easy
deployment to other environments (on-premises or cloud), follow these
instructions. For general use, install locally to leverage your machine's GPU.
We highly recommend to Install InvokeAI locally using [these instructions](index.md)"
!!! tip "For developers"
For container-related development tasks or for enabling easy
deployment to other environments (on-premises or cloud), follow these
instructions.
For general use, install locally to leverage your machine's GPU.
## Why containers?
They provide a flexible, reliable way to build and deploy Stable Diffusion.
You'll also use a Docker volume to store the largest model files and image
outputs as a first step in decoupling storage and compute. Future enhancements
can do this for other assets. See [Processes](https://12factor.net/processes)
under the Twelve-Factor App methodology for details on why running applications
in such a stateless fashion is important.
They provide a flexible, reliable way to build and deploy InvokeAI. You'll also
use a Docker volume to store the largest model files and image outputs as a
first step in decoupling storage and compute. Future enhancements can do this
for other assets. See [Processes](https://12factor.net/processes) under the
Twelve-Factor App methodology for details on why running applications in such a
stateless fashion is important.
You can specify the target platform when building the image and running the
container. You'll also need to specify the Stable Diffusion requirements file
that matches the container's OS and the architecture it will run on.
container. You'll also need to specify the InvokeAI requirements file that
matches the container's OS and the architecture it will run on.
Developers on Apple silicon (M1/M2): You
[can't access your GPU cores from Docker containers](https://github.com/pytorch/pytorch/issues/81224)
@ -38,16 +42,19 @@ another environment with NVIDIA GPUs on-premises or in the cloud.
#### Install [Docker](https://github.com/santisbon/guides#docker)
On the Docker Desktop app, go to Preferences, Resources, Advanced. Increase the
CPUs and Memory to avoid this
On the [Docker Desktop app](https://docs.docker.com/get-docker/), go to
Preferences, Resources, Advanced. Increase the CPUs and Memory to avoid this
[Issue](https://github.com/invoke-ai/InvokeAI/issues/342). You may need to
increase Swap and Disk image size too.
#### Get a Huggingface-Token
Go to [Hugging Face](https://huggingface.co/settings/tokens), create a token and
temporary place it somewhere like a open texteditor window (but dont save it!,
only keep it open, we need it in the next step)
Besides the Docker Agent you will need an Account on
[huggingface.co](https://huggingface.co/join).
After you succesfully registered your account, go to
[huggingface.co/settings/tokens](https://huggingface.co/settings/tokens), create
a token and copy it, since you will need in for the next step.
### Setup
@ -65,13 +72,14 @@ created in the last step.
Some Suggestions of variables you may want to change besides the Token:
| Environment-Variable | Description |
| ------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| `HUGGINGFACE_TOKEN="hg_aewirhghlawrgkjbarug2"` | This is the only required variable, without you can't get the checkpoint |
| `ARCH=aarch64` | if you are using a ARM based CPU |
| `INVOKEAI_TAG=yourname/invokeai:latest` | the Container Repository / Tag which will be used |
| `INVOKEAI_CONDA_ENV_FILE=environment-linux-aarch64.yml` | since environment.yml wouldn't work with aarch |
| `INVOKEAI_GIT="-b branchname https://github.com/username/reponame"` | if you want to use your own fork |
| Environment-Variable | Default value | Description |
| ------------------------- | ----------------------------- | ---------------------------------------------------------------------------- |
| `HUGGINGFACE_TOKEN` | No default, but **required**! | This is the only **required** variable, without you can't get the checkpoint |
| `ARCH` | x86_64 | if you are using a ARM based CPU |
| `INVOKEAI_TAG` | invokeai-x86_64 | the Container Repository / Tag which will be used |
| `INVOKEAI_CONDA_ENV_FILE` | environment-lin-cuda.yml | since environment.yml wouldn't work with aarch |
| `INVOKEAI_GIT` | invoke-ai/InvokeAI | the repository to use |
| `INVOKEAI_BRANCH` | main | the branch to checkout |
#### Build the Image
@ -79,25 +87,41 @@ I provided a build script, which is located in `docker-build/build.sh` but still
needs to be executed from the Repository root.
```bash
docker-build/build.sh
./docker-build/build.sh
```
The build Script not only builds the container, but also creates the docker
volume if not existing yet, or if empty it will just download the models. When
it is done you can run the container via the run script
volume if not existing yet, or if empty it will just download the models.
#### Run the Container
After the build process is done, you can run the container via the provided
`docker-build/run.sh` script
```bash
docker-build/run.sh
./docker-build/run.sh
```
When used without arguments, the container will start the website and provide
When used without arguments, the container will start the webserver and provide
you the link to open it. But if you want to use some other parameters you can
also do so.
!!! example ""
```bash
./docker-build/run.sh --from_file tests/validate_pr_prompt.txt
```
The output folder is located on the volume which is also used to store the model.
Find out more about available CLI-Parameters at [features/CLI.md](../features/CLI.md/#arguments)
---
!!! warning "Deprecated"
From here on it is the rest of the previous Docker-Docs, which will still
provide usefull informations for one or the other.
From here on you will find the the previous Docker-Docs, which will still
provide some usefull informations.
## Usage (time to have fun)

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@ -0,0 +1,64 @@
---
title: InvokeAI Installer
---
The InvokeAI installer is a shell script that will install InvokeAI onto a stock
computer running recent versions of Linux, MacOSX or Windows. It will leave you
with a version that runs a stable version of InvokeAI. When a new version of
InvokeAI is released, you will download and reinstall the new version.
If you wish to tinker with unreleased versions of InvokeAI that introduce
potentially unstable new features, you should consider using the
[source installer](INSTALL_SOURCE.md) or one of the
[manual install](INSTALL_MANUAL.md) methods.
**Important Caveats**
- This script does not support AMD GPUs. For Linux AMD support,
please use the manual or source code installer methods.
- This script has difficulty on some Macintosh machines
that have previously been used for Python development due to
conflicting development tools versions. Mac developers may wish
to try the source code installer or one of the manual methods instead.
!!! todo
Before you begin, make sure that you meet
the[hardware requirements](/#hardware-requirements) and has the
appropriate GPU drivers installed. In particular, if you are a Linux user with
an AMD GPU installed, you may need to install the
[ROCm-driver](https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html).
Installation requires roughly 18G of free disk space to load the libraries and
recommended model weights files.
## Steps to Install
1. Download the
[latest release](https://github.com/invoke-ai/InvokeAI/releases/latest) of
InvokeAI's installer for your platform
2. Place the downloaded package someplace where you have plenty of HDD space,
and have full permissions (i.e. `~/` on Lin/Mac; your home folder on Windows)
3. Extract the 'InvokeAI' folder from the downloaded package
4. Open the extracted 'InvokeAI' folder
5. Double-click 'install.bat' (Windows), or 'install.sh' (Lin/Mac) (or run from
a terminal)
6. Follow the prompts
7. After installation, please run the 'invoke.bat' file (on Windows) or
'invoke.sh' file (on Linux/Mac) to start InvokeAI.
## Troubleshooting
If you run into problems during or after installation, the InvokeAI team is
available to help you. Either create an
[Issue](https://github.com/invoke-ai/InvokeAI/issues) at our GitHub site, or
make a request for help on the "bugs-and-support" channel of our
[Discord server](https://discord.gg/ZmtBAhwWhy). We are a 100% volunteer
organization, but typically somebody will be available to help you within 24
hours, and often much sooner.

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@ -0,0 +1,27 @@
---
title: Running InvokeAI on Google Colab using a Jupyter Notebook
---
# THIS NEEDS TO BE FLESHED OUT
## Introduction
We have a [Jupyter
notebook](https://github.com/invoke-ai/InvokeAI/blob/main/notebooks/Stable-Diffusion-local-Windows.ipynb)
with cell-by-cell installation steps. It will download the code in
this repo as one of the steps, so instead of cloning this repo, simply
download the notebook from the link above and load it up in VSCode
(with the appropriate extensions installed)/Jupyter/JupyterLab and
start running the cells one-by-one.
!!! Note "you will need NVIDIA drivers, Python 3.10, and Git installed beforehand"
## Walkthrough
## Updating to newer versions
### Updating the stable version
### Updating to the development version
## Troubleshooting

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@ -0,0 +1,416 @@
---
title: Manual Installation
---
<figure markdown>
# :fontawesome-brands-linux: Linux | :fontawesome-brands-apple: macOS | :fontawesome-brands-windows: Windows
</figure>
!!! warning "This is for advanced Users"
who are already expirienced with using conda or pip
## Introduction
You have two choices for manual installation, the [first one](#Conda_method)
based on the Anaconda3 package manager (`conda`), and
[a second one](#PIP_method) which uses basic Python virtual environment (`venv`)
commands and the PIP package manager. Both methods require you to enter commands
on the terminal, also known as the "console".
On Windows systems you are encouraged to install and use the
[Powershell](https://learn.microsoft.com/en-us/powershell/scripting/install/installing-powershell-on-windows?view=powershell-7.3),
which provides compatibility with Linux and Mac shells and nice features such as
command-line completion.
### Conda method
1. Check that your system meets the
[hardware requirements](index.md#Hardware_Requirements) and has the
appropriate GPU drivers installed. In particular, if you are a Linux user
with an AMD GPU installed, you may need to install the
[ROCm driver](https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html).
InvokeAI does not yet support Windows machines with AMD GPUs due to the lack
of ROCm driver support on this platform.
To confirm that the appropriate drivers are installed, run `nvidia-smi` on
NVIDIA/CUDA systems, and `rocm-smi` on AMD systems. These should return
information about the installed video card.
Macintosh users with MPS acceleration, or anybody with a CPU-only system,
can skip this step.
2. You will need to install Anaconda3 and Git if they are not already
available. Use your operating system's preferred package manager, or
download the installers manually. You can find them here:
- [Anaconda3](https://www.anaconda.com/)
- [git](https://git-scm.com/downloads)
3. Clone the [InvokeAI](https://github.com/invoke-ai/InvokeAI) source code from
GitHub:
```bash
git clone https://github.com/invoke-ai/InvokeAI.git
```
This will create InvokeAI folder where you will follow the rest of the
steps.
4. Enter the newly-created InvokeAI folder:
```bash
cd InvokeAI
```
From this step forward make sure that you are working in the InvokeAI
directory!
5. Select the appropriate environment file:
We have created a series of environment files suited for different operating
systems and GPU hardware. They are located in the
`environments-and-requirements` directory:
<figure markdown>
| filename | OS |
| :----------------------: | :----------------------------: |
| environment-lin-amd.yml | Linux with an AMD (ROCm) GPU |
| environment-lin-cuda.yml | Linux with an NVIDIA CUDA GPU |
| environment-mac.yml | Macintosh |
| environment-win-cuda.yml | Windows with an NVIDA CUDA GPU |
</figure>
Choose the appropriate environment file for your system and link or copy it
to `environment.yml` in InvokeAI's top-level directory. To do so, run
following command from the repository-root:
!!! Example ""
=== "Macintosh and Linux"
!!! todo "Replace `xxx` and `yyy` with the appropriate OS and GPU codes as seen in the table above"
```bash
ln -sf environments-and-requirements/environment-xxx-yyy.yml environment.yml
```
When this is done, confirm that a file `environment.yml` has been linked in
the InvokeAI root directory and that it points to the correct file in the
`environments-and-requirements`.
```bash
ls -la
```
=== "Windows"
!!! todo " Since it requires admin privileges to create links, we will use the copy command to create your `environment.yml`"
```cmd
copy environments-and-requirements\environment-win-cuda.yml environment.yml
```
Afterwards verify that the file `environment.yml` has been created, either via the
explorer or by using the command `dir` from the terminal
```cmd
dir
```
!!! warning "Do not try to run conda on directly on the subdirectory environments file. This won't work. Instead, copy or link it to the top-level directory as shown."
6. Create the conda environment:
```bash
conda env update
```
This will create a new environment named `invokeai` and install all InvokeAI
dependencies into it. If something goes wrong you should take a look at
[troubleshooting](#troubleshooting).
7. Activate the `invokeai` environment:
In order to use the newly created environment you will first need to
activate it
```bash
conda activate invokeai
```
Your command-line prompt should change to indicate that `invokeai` is active
by prepending `(invokeai)`.
8. Pre-Load the model weights files:
!!! tip
If you have already downloaded the weights file(s) for another Stable
Diffusion distribution, you may skip this step (by selecting "skip" when
prompted) and configure InvokeAI to use the previously-downloaded files. The
process for this is described in [here](INSTALLING_MODELS.md).
```bash
python scripts/preload_models.py
```
The script `preload_models.py` will interactively guide you through the
process of downloading and installing the weights files needed for InvokeAI.
Note that the main Stable Diffusion weights file is protected by a license
agreement that you have to agree to. The script will list the steps you need
to take to create an account on the site that hosts the weights files,
accept the agreement, and provide an access token that allows InvokeAI to
legally download and install the weights files.
If you get an error message about a module not being installed, check that
the `invokeai` environment is active and if not, repeat step 5.
9. Run the command-line- or the web- interface:
!!! example ""
!!! warning "Make sure that the conda environment is activated, which should create `(invokeai)` in front of your prompt!"
=== "CLI"
```bash
python scripts/invoke.py
```
=== "local Webserver"
```bash
python scripts/invoke.py --web
```
=== "Public Webserver"
```bash
python scripts/invoke.py --web --host 0.0.0.0
```
If you choose the run the web interface, point your browser at
http://localhost:9090 in order to load the GUI.
10. Render away!
Browse the [features](../features/CLI.md) section to learn about all the things you
can do with InvokeAI.
Note that some GPUs are slow to warm up. In particular, when using an AMD
card with the ROCm driver, you may have to wait for over a minute the first
time you try to generate an image. Fortunately, after the warm up period
rendering will be fast.
11. Subsequently, to relaunch the script, be sure to run "conda activate
invokeai", enter the `InvokeAI` directory, and then launch the invoke
script. If you forget to activate the 'invokeai' environment, the script
will fail with multiple `ModuleNotFound` errors.
## Updating to newer versions of the script
This distribution is changing rapidly. If you used the `git clone` method
(step 5) to download the InvokeAI directory, then to update to the latest and
greatest version, launch the Anaconda window, enter `InvokeAI` and type:
```bash
git pull
conda env update
python scripts/preload_models.py --no-interactive #optional
```
This will bring your local copy into sync with the remote one. The last step may
be needed to take advantage of new features or released models. The
`--no-interactive` flag will prevent the script from prompting you to download
the big Stable Diffusion weights files.
## pip Install
To install InvokeAI with only the PIP package manager, please follow these
steps:
1. Make sure you are using Python 3.9 or higher. The rest of the install
procedure depends on this:
```bash
python -V
```
2. Install the `virtualenv` tool if you don't have it already:
```bash
pip install virtualenv
```
3. From within the InvokeAI top-level directory, create and activate a virtual
environment named `invokeai`:
```bash
virtualenv invokeai
source invokeai/bin/activate
```
4. Pick the correct `requirements*.txt` file for your hardware and operating
system.
We have created a series of environment files suited for different operating
systems and GPU hardware. They are located in the
`environments-and-requirements` directory:
<figure markdown>
| filename | OS |
| :---------------------------------: | :-------------------------------------------------------------: |
| requirements-lin-amd.txt | Linux with an AMD (ROCm) GPU |
| requirements-lin-arm64.txt | Linux running on arm64 systems |
| requirements-lin-cuda.txt | Linux with an NVIDIA (CUDA) GPU |
| requirements-mac-mps-cpu.txt | Macintoshes with MPS acceleration |
| requirements-lin-win-colab-cuda.txt | Windows with an NVIDA (CUDA) GPU<br>(supports Google Colab too) |
</figure>
Select the appropriate requirements file, and make a link to it from
`requirements.txt` in the top-level InvokeAI directory. The command to do
this from the top-level directory is:
!!! example ""
=== "Macintosh and Linux"
!!! info "Replace `xxx` and `yyy` with the appropriate OS and GPU codes."
```bash
ln -sf environments-and-requirements/requirements-xxx-yyy.txt requirements.txt
```
=== "Windows"
!!! info "on Windows, admin privileges are required to make links, so we use the copy command instead"
```cmd
copy environments-and-requirements\requirements-lin-win-colab-cuda.txt requirements.txt
```
!!! warning
Please do not link or copy `environments-and-requirements/requirements-base.txt`.
This is a base requirements file that does not have the platform-specific
libraries. Also, be sure to link or copy the platform-specific file to
a top-level file named `requirements.txt` as shown here. Running pip on
a requirements file in a subdirectory will not work as expected.
When this is done, confirm that a file named `requirements.txt` has been
created in the InvokeAI root directory and that it points to the correct
file in `environments-and-requirements`.
5. Run PIP
Be sure that the `invokeai` environment is active before doing this:
```bash
pip install --prefer-binary -r requirements.txt
```
---
## Troubleshooting
Here are some common issues and their suggested solutions.
### Conda
#### Conda fails before completing `conda update`
The usual source of these errors is a package incompatibility. While we have
tried to minimize these, over time packages get updated and sometimes introduce
incompatibilities.
We suggest that you search
[Issues](https://github.com/invoke-ai/InvokeAI/issues) or the "bugs-and-support"
channel of the [InvokeAI Discord](https://discord.gg/ZmtBAhwWhy).
You may also try to install the broken packages manually using PIP. To do this,
activate the `invokeai` environment, and run `pip install` with the name and
version of the package that is causing the incompatibility. For example:
```bash
pip install test-tube==0.7.5
```
You can keep doing this until all requirements are satisfied and the `invoke.py`
script runs without errors. Please report to
[Issues](https://github.com/invoke-ai/InvokeAI/issues) what you were able to do
to work around the problem so that others can benefit from your investigation.
#### `preload_models.py` or `invoke.py` crashes at an early stage
This is usually due to an incomplete or corrupted Conda install. Make sure you
have linked to the correct environment file and run `conda update` again.
If the problem persists, a more extreme measure is to clear Conda's caches and
remove the `invokeai` environment:
```bash
conda deactivate
conda env remove -n invokeai
conda clean -a
conda update
```
This removes all cached library files, including ones that may have been
corrupted somehow. (This is not supposed to happen, but does anyway).
#### `invoke.py` crashes at a later stage
If the CLI or web site had been working ok, but something unexpected happens
later on during the session, you've encountered a code bug that is probably
unrelated to an install issue. Please search
[Issues](https://github.com/invoke-ai/InvokeAI/issues), file a bug report, or
ask for help on [Discord](https://discord.gg/ZmtBAhwWhy)
#### My renders are running very slowly
You may have installed the wrong torch (machine learning) package, and the
system is running on CPU rather than the GPU. To check, look at the log messages
that appear when `invoke.py` is first starting up. One of the earlier lines
should say `Using device type cuda`. On AMD systems, it will also say "cuda",
and on Macintoshes, it should say "mps". If instead the message says it is
running on "cpu", then you may need to install the correct torch library.
You may be able to fix this by installing a different torch library. Here are
the magic incantations for Conda and PIP.
!!! todo "For CUDA systems"
- conda
```bash
conda install pytorch torchvision torchaudio pytorch-cuda=11.6 -c pytorch -c nvidia
```
- pip
```bash
pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu116
```
!!! todo "For AMD systems"
- conda
```bash
conda activate invokeai
pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/rocm5.2/
```
- pip
```bash
pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/rocm5.2/
```
More information and troubleshooting tips can be found at https://pytorch.org.

View File

@ -0,0 +1,17 @@
---
title: Installing InvokeAI with the Pre-Compiled PIP Installer
---
# THIS NEEDS TO BE FLESHED OUT
## Introduction
## Walkthrough
## Updating to newer versions
### Updating the stable version
### Updating to the development version
## Troubleshooting

View File

@ -0,0 +1,156 @@
---
title: Source Installer
---
# The InvokeAI Source Installer
## Introduction
The source installer is a shell script that attempts to automate every step
needed to install and run InvokeAI on a stock computer running recent versions
of Linux, MacOS or Windows. It will leave you with a version that runs a stable
version of InvokeAI with the option to upgrade to experimental versions later.
It is not as foolproof as the [InvokeAI installer](INSTALL_INVOKE.md)
Before you begin, make sure that you meet the
[hardware requirements](index.md#Hardware_Requirements) and has the appropriate
GPU drivers installed. In particular, if you are a Linux user with an AMD GPU
installed, you may need to install the
[ROCm driver](https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html).
Installation requires roughly 18G of free disk space to load the libraries and
recommended model weights files.
## Walk through
Though there are multiple steps, there really is only one click involved to kick
off the process.
1. The source installer is distributed in ZIP files. Go to the
[latest release](https://github.com/invoke-ai/InvokeAI/releases/latest), and
look for a series of files named:
- invokeAI-src-installer-mac.zip
- invokeAI-src-installer-windows.zip
- invokeAI-src-installer-linux.zip
Download the one that is appropriate for your operating system.
2. Unpack the zip file into a directory that has at least 18G of free space. Do
_not_ unpack into a directory that has an earlier version of InvokeAI.
This will create a new directory named "InvokeAI". This example shows how
this would look using the `unzip` command-line tool, but you may use any
graphical or command-line Zip extractor:
```cmd
C:\Documents\Linco> unzip invokeAI-windows.zip
Archive: C: \Linco\Downloads\invokeAI-linux.zip
creating: invokeAI\
inflating: invokeAI\install.bat
inflating: invokeAI\readme.txt
```
3. If you are using a desktop GUI, double-click the installer file. It will be
named `install.bat` on Windows systems and `install.sh` on Linux and
Macintosh systems.
4. Alternatively, form the command line, run the shell script or .bat file:
```cmd
C:\Documents\Linco> cd invokeAI
C:\Documents\Linco\invokeAI> install.bat
```
5. Sit back and let the install script work. It will install various binary
requirements including Conda, Git and Python, then download the current
InvokeAI code and install it along with its dependencies.
6. After installation completes, the installer will launch a script called
`preload_models.py`, which will guide you through the first-time process of
selecting one or more Stable Diffusion model weights files, downloading and
configuring them.
Note that the main Stable Diffusion weights file is protected by a license
agreement that you must agree to in order to use. The script will list the
steps you need to take to create an account on the official site that hosts
the weights files, accept the agreement, and provide an access token that
allows InvokeAI to legally download and install the weights files.
If you have already downloaded the weights file(s) for another Stable
Diffusion distribution, you may skip this step (by selecting "skip" when
prompted) and configure InvokeAI to use the previously-downloaded files. The
process for this is described in [Installing Models](INSTALLING_MODELS.md).
7. The script will now exit and you'll be ready to generate some images. The
invokeAI directory will contain numerous files. Look for a shell script
named `invoke.sh` (Linux/Mac) or `invoke.bat` (Windows). Launch the script
by double-clicking it or typing its name at the command-line:
```cmd
C:\Documents\Linco> cd invokeAI
C:\Documents\Linco\invokeAI> invoke.bat
```
The `invoke.bat` (`invoke.sh`) script will give you the choice of starting (1)
the command-line interface, or (2) the web GUI. If you start the latter, you can
load the user interface by pointing your browser at http://localhost:9090.
The `invoke` script also offers you a third option labeled "open the developer
console". If you choose this option, you will be dropped into a command-line
interface in which you can run python commands directly, access developer tools,
and launch InvokeAI with customized options. To do the latter, you would launch
the script `scripts/invoke.py` as shown in this example:
```cmd
python scripts/invoke.py --web --max_load_models=3 \
--model=waifu-1.3 --steps=30 --outdir=C:/Documents/AIPhotos
```
These options are described in detail in the
[Command-Line Interface](../features/CLI.md) documentation.
## Updating to newer versions
This section describes how to update InvokeAI to new versions of the software.
### Updating the stable version
This distribution is changing rapidly, and we add new features on a daily basis.
To update to the latest released version (recommended), run the `update.sh`
(Linux/Mac) or `update.bat` (Windows) scripts. This will fetch the latest
release and re-run the `preload_models` script to download any updated models
files that may be needed. You can also use this to add additional models that
you did not select at installation time.
### Updating to the development version
There may be times that there is a feature in the `development` branch of
InvokeAI that you'd like to take advantage of. Or perhaps there is a branch that
corrects an annoying bug. To do this, you will use the developer's console.
From within the invokeAI directory, run the command `invoke.sh` (Linux/Mac) or
`invoke.bat` (Windows) and selection option (3) to open the developers console.
Then run the following command to get the `development branch`:
```bash
git checkout development
git pull
conda env update
```
You can now close the developer console and run `invoke` as before. If you get
complaints about missing models, then you may need to do the additional step of
running `preload_models.py`. This happens relatively infrequently. To do this,
simply open up the developer's console again and type
`python scripts/preload_models.py`.
## Troubleshooting
If you run into problems during or after installation, the InvokeAI team is
available to help you. Either create an
[Issue](https://github.com/invoke-ai/InvokeAI/issues) at our GitHub site, or
make a request for help on the "bugs-and-support" channel of our
[Discord server](https://discord.gg/ZmtBAhwWhy). We are a 100% volunteer
organization, but typically somebody will be available to help you within 24
hours, and often much sooner.

View File

@ -0,0 +1,62 @@
---
title: Overview
---
We offer several ways to install InvokeAI, each one suited to your
experience and preferences.
1. [InvokeAI installer](INSTALL_INVOKE.md)
This is a installer script that installs InvokeAI and all the
third party libraries it depends on. When a new version of
InvokeAI is released, you will download and reinstall the new
version.
This installer is designed for people who want the system to "just
work", don't have an interest in tinkering with it, and do not
care about upgrading to unreleased experimental features.
**Important Caveats**
- This script does not support AMD GPUs. For Linux AMD support,
please use the manual or source code installer methods.
- This script has difficulty on some Macintosh machines
that have previously been used for Python development due to
conflicting development tools versions. Mac developers may wish
to try the source code installer or one of the manual methods instead.
2. [Source code installer](INSTALL_SOURCE.md)
This is a script that will install InvokeAI and all its essential
third party libraries. In contrast to the previous installer, it
includes access to a "developer console" which will allow you to
access experimental features on the development branch.
This method is recommended for individuals who are wish to stay
on the cutting edge of InvokeAI development and are not afraid
of occasional breakage.
3. [Manual Installation](INSTALL_MANUAL.md)
In this method you will manually run the commands needed to install
InvokeAI and its dependencies. We offer two recipes: one suited to
those who prefer the `conda` tool, and one suited to those who prefer
`pip` and Python virtual environments.
This method is recommended for users who have previously used `conda`
or `pip` in the past, developers, and anyone who wishes to remain on
the cutting edge of future InvokeAI development and is willing to put
up with occasional glitches and breakage.
4. [Docker Installation](INSTALL_DOCKER.md)
We also offer a method for creating Docker containers containing
InvokeAI and its dependencies. This method is recommended for
individuals with experience with Docker containers and understand
the pluses and minuses of a container-based install.
5. [Jupyter Notebooks Installation](INSTALL_JUPYTER.md)
This method is suitable for running InvokeAI on a Google Colab
account. It is recommended for individuals who have previously
worked on the Colab and are comfortable with the Jupyter notebook
environment.

View File

@ -42,14 +42,25 @@ title: Manual Installation, Linux
```
5. Use anaconda to copy necessary python packages, create a new python
environment named `invokeai` and activate the environment.
environment named `invokeai` and then activate the environment.
```bash
(base) rm -rf src # (this is a precaution in case there is already a src directory)
(base) ~/InvokeAI$ conda env create
(base) ~/InvokeAI$ conda activate invokeai
(invokeai) ~/InvokeAI$
```
!!! todo "For systems with a CUDA (Nvidia) card:"
```bash
(base) rm -rf src # (this is a precaution in case there is already a src directory)
(base) ~/InvokeAI$ conda env create -f environment-cuda.yml
(base) ~/InvokeAI$ conda activate invokeai
(invokeai) ~/InvokeAI$
```
!!! todo "For systems with an AMD card (using ROCm driver):"
```bash
(base) rm -rf src # (this is a precaution in case there is already a src directory)
(base) ~/InvokeAI$ conda env create -f environment-AMD.yml
(base) ~/InvokeAI$ conda activate invokeai
(invokeai) ~/InvokeAI$
```
After these steps, your command prompt will be prefixed by `(invokeai)` as
shown above.

View File

@ -13,22 +13,9 @@ one of the steps, so instead of cloning this repo, simply download the notebook
from the link above and load it up in VSCode (with the appropriate extensions
installed)/Jupyter/JupyterLab and start running the cells one-by-one.
Note that you will need NVIDIA drivers, Python 3.10, and Git installed
beforehand - simplified
[step-by-step instructions](https://github.com/invoke-ai/InvokeAI/wiki/Easy-peasy-Windows-install)
are available in the wiki (you'll only need steps 1, 2, & 3 ).
Note that you will need NVIDIA drivers, Python 3.10, and Git installed beforehand.
## **Manual Install**
### **pip**
See
[Easy-peasy Windows install](https://github.com/invoke-ai/InvokeAI/wiki/Easy-peasy-Windows-install)
in the wiki
---
### **Conda**
## **Manual Install with Conda**
1. Install Anaconda3 (miniconda3 version) from [here](https://docs.anaconda.com/anaconda/install/windows/)
@ -52,23 +39,29 @@ in the wiki
cd InvokeAI
```
6. Run the following two commands:
6. Run the following commands:
```batch title="step 6a"
conda env create
```
!!! todo "For systems with a CUDA (Nvidia) card:"
```batch title="step 6b"
conda activate invokeai
```
```bash
rmdir src # (this is a precaution in case there is already a src directory)
conda env create -f environment-cuda.yml
conda activate invokeai
(invokeai)>
```
!!! todo "For systems with an AMD card (using ROCm driver):"
```bash
rmdir src # (this is a precaution in case there is already a src directory)
conda env create -f environment-AMD.yml
conda activate invokeai
(invokeai)>
```
This will install all python requirements and activate the "invokeai" environment
which sets PATH and other environment variables properly.
Note that the long form of the first command is `conda env create -f environment.yml`. If the
environment file isn't specified, conda will default to `environment.yml`. You will need
to provide the `-f` option if you wish to load a different environment file at any point.
7. Load the big stable diffusion weights files and a couple of smaller machine-learning models:
```bash

View File

@ -4,40 +4,41 @@ channels:
- conda-forge
- defaults
dependencies:
- python=3.10
- pip>=22.2.2
- albumentations=0.4.3
- cudatoolkit
- pytorch
- torchvision
- numpy=1.23
- imageio=2.21
- opencv=4.6
- pillow=8.*
- einops=0.3.0
- eventlet
- flask-socketio=5.3.0
- flask=2.1.*
- flask_cors=3.0.10
- flask-socketio=5.3.0
- send2trash=1.8.0
- eventlet
- albumentations=0.4.3
- pudb=2019.2
- imageio-ffmpeg=0.4.2
- pytorch-lightning=1.7.7
- streamlit
- einops=0.3.0
- imageio=2.9.0
- kornia=0.6
- torchmetrics=0.7.0
- transformers=4.23
- torch-fidelity=0.3.0
- numpy=1.19
- opencv=4.6.0
- pillow=8.*
- pip>=22.2.2
- pudb=2019.2
- python=3.9.*
- pytorch
- pytorch-lightning=1.7.7
- send2trash=1.8.0
- streamlit
- tokenizers>=0.11.1,!=0.11.3,<0.13
- torch-fidelity=0.3.0
- torchmetrics=0.7.0
- torchvision
- transformers=4.21.3
- pip:
- dependency_injector==4.40.0
- getpass_asterisk
- omegaconf==2.1.1
- pyreadline3
- realesrgan
- taming-transformers-rom1504
- test-tube>=0.7.5
- git+https://github.com/openai/CLIP.git@main#egg=clip
- git+https://github.com/invoke-ai/k-diffusion.git@mps#egg=k_diffusion
- git+https://github.com/invoke-ai/Real-ESRGAN.git#egg=realesrgan
- git+https://github.com/invoke-ai/GFPGAN.git#egg=gfpgan
- git+https://github.com/invoke-ai/clipseg.git@models-rename#egg=clipseg
- git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k_diffusion
- git+https://github.com/invoke-ai/clipseg.git@relaxed-python-requirement#egg=clipseg
- git+https://github.com/invoke-ai/GFPGAN#egg=gfpgan
- -e .

View File

@ -0,0 +1,45 @@
name: invokeai
channels:
- pytorch
- conda-forge
- defaults
dependencies:
- python>=3.9
- pip=22.2.2
- numpy=1.23.3
- pip:
- --extra-index-url https://download.pytorch.org/whl/rocm5.2/
- albumentations==0.4.3
- dependency_injector==4.40.0
- diffusers==0.6.0
- einops==0.3.0
- eventlet
- flask==2.1.3
- flask_cors==3.0.10
- flask_socketio==5.3.0
- getpass_asterisk
- imageio-ffmpeg==0.4.2
- imageio==2.9.0
- kornia==0.6.0
- omegaconf==2.2.3
- opencv-python==4.5.5.64
- pillow==9.2.0
- pudb==2019.2
- pyreadline3
- pytorch-lightning==1.7.7
- realesrgan
- send2trash==1.8.0
- streamlit==1.12.0
- taming-transformers-rom1504
- test-tube>=0.7.5
- torch
- torch-fidelity==0.3.0
- torchaudio
- torchmetrics==0.7.0
- torchvision
- transformers==4.21.3
- git+https://github.com/openai/CLIP.git@main#egg=clip
- git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k_diffusion
- git+https://github.com/invoke-ai/clipseg.git@relaxed-python-requirement#egg=clipseg
- git+https://github.com/invoke-ai/GFPGAN#egg=gfpgan
- -e .

View File

@ -13,32 +13,33 @@ dependencies:
- cudatoolkit=11.6
- pip:
- albumentations==0.4.3
- opencv-python==4.5.5.64
- pudb==2019.2
- imageio==2.9.0
- imageio-ffmpeg==0.4.2
- pytorch-lightning==1.7.7
- omegaconf==2.2.3
- test-tube>=0.7.5
- streamlit==1.12.0
- send2trash==1.8.0
- pillow==9.2.0
- einops==0.3.0
- pyreadline3
- torch-fidelity==0.3.0
- transformers==4.21.3
- dependency_injector==4.40.0
- diffusers==0.6.0
- torchmetrics==0.7.0
- flask==2.1.3
- flask_socketio==5.3.0
- flask_cors==3.0.10
- einops==0.3.0
- eventlet
- flask==2.1.3
- flask_cors==3.0.10
- flask_socketio==5.3.0
- getpass_asterisk
- imageio-ffmpeg==0.4.2
- imageio==2.9.0
- kornia==0.6.0
- omegaconf==2.2.3
- opencv-python==4.5.5.64
- pillow==9.2.0
- pudb==2019.2
- pyreadline3
- pytorch-lightning==1.7.7
- realesrgan
- send2trash==1.8.0
- streamlit==1.12.0
- taming-transformers-rom1504
- test-tube>=0.7.5
- torch-fidelity==0.3.0
- torchmetrics==0.7.0
- transformers==4.21.3
- git+https://github.com/openai/CLIP.git@main#egg=clip
- git+https://github.com/invoke-ai/k-diffusion.git@mps#egg=k_diffusion
- git+https://github.com/invoke-ai/Real-ESRGAN.git#egg=realesrgan
- git+https://github.com/invoke-ai/GFPGAN.git#egg=gfpgan
- git+https://github.com/invoke-ai/clipseg.git@models-rename#egg=clipseg
- git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k_diffusion
- git+https://github.com/invoke-ai/clipseg.git@relaxed-python-requirement#egg=clipseg
- git+https://github.com/invoke-ai/GFPGAN#egg=gfpgan
- -e .

View File

@ -58,7 +58,7 @@ dependencies:
- git+https://github.com/invoke-ai/k-diffusion.git@mps#egg=k_diffusion
- git+https://github.com/invoke-ai/Real-ESRGAN.git#egg=realesrgan
- git+https://github.com/invoke-ai/GFPGAN.git#egg=gfpgan
- git+https://github.com/invoke-ai/clipseg.git@models-rename#egg=clipseg
- git+https://github.com/invoke-ai/clipseg.git@relaxed-python-requirement#egg=clipseg
- -e .
variables:
PYTORCH_ENABLE_MPS_FALLBACK: 1

View File

@ -0,0 +1,46 @@
name: invokeai
channels:
- pytorch
- conda-forge
- defaults
dependencies:
- python>=3.9
- pip=22.2.2
- numpy=1.23.3
- torchvision=0.13.1
- torchaudio=0.12.1
- pytorch=1.12.1
- cudatoolkit=11.6
- pip:
- albumentations==0.4.3
- basicsr==1.4.1
- dependency_injector==4.40.0
- diffusers==0.6.0
- einops==0.3.0
- eventlet
- flask==2.1.3
- flask_cors==3.0.10
- flask_socketio==5.3.0
- getpass_asterisk
- imageio-ffmpeg==0.4.2
- imageio==2.9.0
- kornia==0.6.0
- omegaconf==2.2.3
- opencv-python==4.5.5.64
- pillow==9.2.0
- pudb==2019.2
- pyreadline3
- pytorch-lightning==1.7.7
- realesrgan
- send2trash==1.8.0
- streamlit==1.12.0
- taming-transformers-rom1504
- test-tube>=0.7.5
- torch-fidelity==0.3.0
- torchmetrics==0.7.0
- transformers==4.21.3
- git+https://github.com/openai/CLIP.git@main#egg=clip
- git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k_diffusion
- git+https://github.com/invoke-ai/clipseg.git@relaxed-python-requirement#egg=clipseg
- git+https://github.com/invoke-ai/GFPGAN#egg=gfpgan
- -e .

View File

@ -1,41 +1,36 @@
--prefer-binary
# pip will resolve the version which matches torch
albumentations
dependency_injector==4.40.0
diffusers
einops
eventlet
flask==2.1.3
flask_cors==3.0.10
flask_socketio==5.3.0
flaskwebgui==0.3.7
getpass_asterisk
huggingface-hub
imageio-ffmpeg
imageio
imageio-ffmpeg
kornia
# pip will resolve the version which matches torch
numpy
omegaconf
opencv-python
pillow
pip>=22
pudb
pytorch-lightning==1.7.7
scikit-image>=0.19
streamlit
pyreadline3
# "CompVis/taming-transformers" IS NOT INSTALLABLE
# This is a drop-in replacement
pytorch-lightning==1.7.7
realesrgan
scikit-image>=0.19
send2trash
streamlit
taming-transformers-rom1504
test-tube
torch-fidelity
torchmetrics
transformers==4.21.*
flask==2.1.3
flask_socketio==5.3.0
flask_cors==3.0.10
flaskwebgui==0.3.7
send2trash
dependency_injector==4.40.0
eventlet
realesrgan
diffusers
git+https://github.com/openai/CLIP.git@main#egg=clip
git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k-diffusion
git+https://github.com/invoke-ai/Real-ESRGAN.git#egg=realesrgan
git+https://github.com/invoke-ai/GFPGAN.git#egg=gfpgan
git+https://github.com/invoke-ai/clipseg.git@models-rename#egg=clipseg
git+https://github.com/invoke-ai/clipseg.git@relaxed-python-requirement#egg=clipseg
git+https://github.com/invoke-ai/GFPGAN#egg=gfpgan

View File

@ -1,4 +1,4 @@
-r requirements.txt
-r environments-and-requirements/requirements-base.txt
# Get hardware-appropriate torch/torchvision
--extra-index-url https://download.pytorch.org/whl/rocm5.1.1 --trusted-host https://download.pytorch.org

View File

@ -0,0 +1,3 @@
--pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cpu
-r environments-and-requirements/requirements-base.txt
-e .

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@ -0,0 +1,2 @@
-r environments-and-requirements/requirements-base.txt
-e .

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@ -1,4 +1,4 @@
-r requirements.txt
-r environments-and-requirements/requirements-base.txt
protobuf==3.19.6
torch<1.13.0

View File

@ -1,7 +1,8 @@
-r requirements.txt
-r environments-and-requirements/requirements-base.txt
# Get hardware-appropriate torch/torchvision
--extra-index-url https://download.pytorch.org/whl/cu116 --trusted-host https://download.pytorch.org
basicsr==1.4.1
torch==1.12.1
torchvision==0.13.1
-e .

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@ -6,7 +6,7 @@
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>InvokeAI - A Stable Diffusion Toolkit</title>
<link rel="shortcut icon" type="icon" href="./assets/favicon.0d253ced.ico" />
<script type="module" crossorigin src="./assets/index.1fc0290b.js"></script>
<script type="module" crossorigin src="./assets/index.a8ba2a6c.js"></script>
<link rel="stylesheet" href="./assets/index.40a72c80.css">
</head>

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frontend/package-lock.json generated

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@ -1,4 +1,4 @@
import { IconButton, Image } from '@chakra-ui/react';
import { IconButton, Image, Spinner } from '@chakra-ui/react';
import { useState } from 'react';
import { FaAngleLeft, FaAngleRight } from 'react-icons/fa';
import { RootState, useAppDispatch, useAppSelector } from '../../app/store';
@ -30,7 +30,6 @@ export const imagesSelector = createSelector(
return {
imageToDisplay: intermediateImage ? intermediateImage : currentImage,
isIntermediate: intermediateImage,
currentCategory,
isOnFirstImage: currentImageIndex === 0,
isOnLastImage:
@ -56,7 +55,6 @@ export default function CurrentImagePreview() {
isOnLastImage,
shouldShowImageDetails,
imageToDisplay,
isIntermediate,
} = useAppSelector(imagesSelector);
const [shouldShowNextPrevButtons, setShouldShowNextPrevButtons] =
@ -83,8 +81,8 @@ export default function CurrentImagePreview() {
{imageToDisplay && (
<Image
src={imageToDisplay.url}
width={isIntermediate ? imageToDisplay.width : undefined}
height={isIntermediate ? imageToDisplay.height : undefined}
width={imageToDisplay.width}
height={imageToDisplay.height}
/>
)}
{!shouldShowImageDetails && (

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@ -1,22 +1,29 @@
#!/bin/bash
#!/usr/bin/env bash
cd "$(dirname "${BASH_SOURCE[0]}")"
set -euo pipefail
IFS=$'\n\t'
echo "Be certain that you're in the 'installer' directory before continuing."
read -p "Press any key to continue, or CTRL-C to exit..."
# make the installer zip for linux and mac
rm -rf invokeAI
mkdir -p invokeAI
cp install.sh invokeAI
cp readme.txt invokeAI
rm -rf InvokeAI
mkdir -p InvokeAI
cp install.sh InvokeAI
cp readme.txt InvokeAI
zip -r invokeAI-linux.zip invokeAI
zip -r invokeAI-mac.zip invokeAI
zip -r InvokeAI-linux.zip InvokeAI
zip -r InvokeAI-mac.zip InvokeAI
# make the installer zip for windows
rm -rf invokeAI
mkdir -p invokeAI
cp install.bat invokeAI
cp readme.txt invokeAI
rm -rf InvokeAI
mkdir -p InvokeAI
cp install.bat InvokeAI
cp readme.txt InvokeAI
cp WinLongPathsEnabled.reg InvokeAI
zip -r invokeAI-windows.zip invokeAI
zip -r InvokeAI-windows.zip InvokeAI
echo "The installer zips are ready to be distributed.."
rm -rf InvokeAI
echo "The installer zips are ready for distribution."

View File

@ -1,115 +1,164 @@
@echo off
@rem This script will install git and conda (if not found on the PATH variable)
@rem This script will install git (if not found on the PATH variable)
@rem using micromamba (an 8mb static-linked single-file binary, conda replacement).
@rem For users who already have git and conda, this step will be skipped.
@rem For users who already have git, this step will be skipped.
@rem Next, it'll checkout the project's git repo, if necessary.
@rem Finally, it'll create the conda environment and preload the models.
@rem Next, it'll download the project's source code.
@rem Then it will download a self-contained, standalone Python and unpack it.
@rem Finally, it'll create the Python virtual environment and preload the models.
@rem This enables a user to install this project without manually installing conda and git.
@rem This enables a user to install this project without manually installing git or Python
echo "Installing InvokeAI.."
echo.
echo ***** Installing InvokeAI.. *****
@rem config
set MAMBA_ROOT_PREFIX=%cd%\installer_files\mamba
set PATH=c:\windows\system32
@rem Config
set INSTALL_ENV_DIR=%cd%\installer_files\env
@rem https://mamba.readthedocs.io/en/latest/installation.html
set MICROMAMBA_DOWNLOAD_URL=https://github.com/cmdr2/stable-diffusion-ui/releases/download/v1.1/micromamba.exe
set REPO_URL=https://github.com/invoke-ai/InvokeAI.git
set umamba_exists=F
@rem Change the download URL to an InvokeAI repo's release URL
@rem figure out whether git and conda needs to be installed
if exist "%INSTALL_ENV_DIR%" set PATH=%INSTALL_ENV_DIR%;%INSTALL_ENV_DIR%\Library\bin;%INSTALL_ENV_DIR%\Scripts;%INSTALL_ENV_DIR%\Library\usr\bin;%PATH%
set RELEASE_URL=https://github.com/invoke-ai/InvokeAI
set RELEASE_SOURCEBALL=/archive/refs/heads/v2.1.3.tar.gz
set PYTHON_BUILD_STANDALONE_URL=https://github.com/indygreg/python-build-standalone/releases/download
set PYTHON_BUILD_STANDALONE=20221002/cpython-3.10.7+20221002-x86_64-pc-windows-msvc-shared-install_only.tar.gz
set PACKAGES_TO_INSTALL=
call conda --version >.tmp1 2>.tmp2
if "%ERRORLEVEL%" NEQ "0" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% conda
call git --version >.tmp1 2>.tmp2
if "%ERRORLEVEL%" NEQ "0" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% git
call "%MAMBA_ROOT_PREFIX%\micromamba.exe" --version >.tmp1 2>.tmp2
if "%ERRORLEVEL%" EQU "0" set umamba_exists=T
@rem Cleanup
del /q .tmp1 .tmp2
@rem (if necessary) install git and conda into a contained environment
@rem (if necessary) install git into a contained environment
if "%PACKAGES_TO_INSTALL%" NEQ "" (
@rem download micromamba
if "%umamba_exists%" == "F" (
echo "Downloading micromamba from %MICROMAMBA_DOWNLOAD_URL% to %MAMBA_ROOT_PREFIX%\micromamba.exe"
echo ***** Downloading micromamba from %MICROMAMBA_DOWNLOAD_URL% to micromamba.exe *****
mkdir "%MAMBA_ROOT_PREFIX%"
call curl -L "%MICROMAMBA_DOWNLOAD_URL%" > "%MAMBA_ROOT_PREFIX%\micromamba.exe"
call curl -L "%MICROMAMBA_DOWNLOAD_URL%" > micromamba.exe
@rem test the mamba binary
echo Micromamba version:
call "%MAMBA_ROOT_PREFIX%\micromamba.exe" --version
)
@rem test the mamba binary
echo ***** Micromamba version: *****
call micromamba.exe --version
@rem create the installer env
if not exist "%INSTALL_ENV_DIR%" (
call "%MAMBA_ROOT_PREFIX%\micromamba.exe" create -y --prefix "%INSTALL_ENV_DIR%"
call micromamba.exe create -y --prefix "%INSTALL_ENV_DIR%"
)
echo "Packages to install:%PACKAGES_TO_INSTALL%"
echo ***** Packages to install:%PACKAGES_TO_INSTALL% *****
call "%MAMBA_ROOT_PREFIX%\micromamba.exe" install -y --prefix "%INSTALL_ENV_DIR%" -c conda-forge %PACKAGES_TO_INSTALL%
call micromamba.exe install -y --prefix "%INSTALL_ENV_DIR%" -c conda-forge %PACKAGES_TO_INSTALL%
if not exist "%INSTALL_ENV_DIR%" (
echo "There was a problem while installing%PACKAGES_TO_INSTALL% using micromamba. Cannot continue."
echo ----- There was a problem while installing "%PACKAGES_TO_INSTALL%" using micromamba. Cannot continue. -----
pause
exit /b
)
)
set PATH=%INSTALL_ENV_DIR%;%INSTALL_ENV_DIR%\Library\bin;%INSTALL_ENV_DIR%\Scripts;%INSTALL_ENV_DIR%\Library\usr\bin;%PATH%
del /q micromamba.exe
@rem get the repo (and load into the current directory)
if not exist ".git" (
call git config --global init.defaultBranch main
call git init
call git remote add origin %REPO_URL%
call git fetch
# call git checkout origin/main -ft
call git checkout origin/release-candidate-2-1 -ft
)
@rem For 'git' only
set PATH=%INSTALL_ENV_DIR%\Library\bin;%PATH%
@rem activate the base env
call conda activate
@rem Download/unpack/clean up InvokeAI release sourceball
set err_msg=----- InvokeAI source download failed -----
curl -L %RELEASE_URL%/%RELEASE_SOURCEBALL% --output InvokeAI.tgz
if %errorlevel% neq 0 goto err_exit
@rem create the environment
call conda env remove -n invokeai
call conda env create
if "%ERRORLEVEL%" NEQ "0" (
echo ""
echo "Something went wrong while installing Python libraries and cannot continue.
echo "Please visit https://invoke-ai.github.io/InvokeAI/#installation for alternative"
echo "installation methods."
echo "Press any key to continue"
pause
exit /b
)
set err_msg=----- InvokeAI source unpack failed -----
tar -zxf InvokeAI.tgz
if %errorlevel% neq 0 goto err_exit
del /q InvokeAI.tgz
set err_msg=----- InvokeAI source copy failed -----
cd InvokeAI-*
xcopy . .. /e /h
if %errorlevel% neq 0 goto err_exit
cd ..
@rem cleanup
for /f %%i in ('dir /b InvokeAI-*') do rd /s /q %%i
rd /s /q .dev_scripts .github docker-build tests
del /q requirements.in requirements-mkdocs.txt shell.nix
echo ***** Unpacked InvokeAI source *****
@rem Download/unpack/clean up python-build-standalone
set err_msg=----- Python download failed -----
curl -L %PYTHON_BUILD_STANDALONE_URL%/%PYTHON_BUILD_STANDALONE% --output python.tgz
if %errorlevel% neq 0 goto err_exit
set err_msg=----- Python unpack failed -----
tar -zxf python.tgz
if %errorlevel% neq 0 goto err_exit
del /q python.tgz
echo ***** Unpacked python-build-standalone *****
@rem create venv
set err_msg=----- problem creating venv -----
.\python\python -E -s -m venv .venv
@rem In reality, the following is ALL that 'activate.bat' does,
@rem aside from setting the prompt, which we don't care about
set PYTHONPATH=
set PATH=.venv\Scripts;%PATH%
if %errorlevel% neq 0 goto err_exit
echo ***** Created Python virtual environment *****
@rem Print venv's Python version
set err_msg=----- problem calling venv's python -----
echo We're running under
.venv\Scripts\python --version
if %errorlevel% neq 0 goto err_exit
set err_msg=----- pip update failed -----
.venv\Scripts\python -m pip install --no-cache-dir --no-warn-script-location --upgrade pip
if %errorlevel% neq 0 goto err_exit
echo ***** Updated pip *****
set err_msg=----- requirements file copy failed -----
copy installer\py3.10-windows-x86_64-cuda-reqs.txt requirements.txt
if %errorlevel% neq 0 goto err_exit
set err_msg=----- main pip install failed -----
.venv\Scripts\python -m pip install --no-cache-dir --no-warn-script-location -r requirements.txt
if %errorlevel% neq 0 goto err_exit
set err_msg=----- clipseg install failed -----
.venv\Scripts\python -m pip install --no-cache-dir --no-warn-script-location git+https://github.com/invoke-ai/clipseg.git@relaxed-python-requirement#egg=clipseg
if %errorlevel% neq 0 goto err_exit
set err_msg=----- InvokeAI setup failed -----
.venv\Scripts\python -m pip install --no-cache-dir --no-warn-script-location -e .
if %errorlevel% neq 0 goto err_exit
echo ***** Installed Python dependencies *****
call conda activate invokeai
@rem preload the models
call python scripts\preload_models.py
if "%ERRORLEVEL%" NEQ "0" (
echo ""
echo "The preload_models.py script crashed or was cancelled."
echo "InvokeAI is not ready to run. To run preload_models.py again,"
echo "run the command 'update.bat' in this directory."
echo "Press any key to continue"
pause
exit /b
)
call .venv\Scripts\python scripts\preload_models.py
set err_msg=----- model download clone failed -----
if %errorlevel% neq 0 goto err_exit
echo ***** Finished downloading models *****
echo ***** Installing invoke.bat ******
copy installer\invoke.bat .\invoke.bat
echo All done! Execute the file invoke.bat in this directory to start InvokeAI
@rem more cleanup
rd /s /q installer installer_files
@rem tell the user their next steps
echo ""
echo "* InvokeAI installed successfully *"
echo "You can now start generating images by double-clicking the 'invoke.bat' file (inside this folder)
echo "Press any key to continue"
pause
exit 0
exit
:err_exit
echo %err_msg%
pause
exit

View File

@ -1,130 +1,211 @@
#!/bin/bash
#!/usr/bin/env bash
# This script will install git and conda (if not found on the PATH variable)
set -euo pipefail
IFS=$'\n\t'
function _err_exit {
if test "$1" -ne 0
then
echo -e "Error code $1; Error caught was '$2'"
read -p "Press any key to exit..."
exit
fi
}
# This script will install git (if not found on the PATH variable)
# using micromamba (an 8mb static-linked single-file binary, conda replacement).
# For users who already have git and conda, this step will be skipped.
# For users who already have git, this step will be skipped.
# Next, it'll checkout the project's git repo, if necessary.
# Finally, it'll create the conda environment and preload the models.
# Next, it'll download the project's source code.
# Then it will download a self-contained, standalone Python and unpack it.
# Finally, it'll create the Python virtual environment and preload the models.
# This enables a user to install this project without manually installing conda and git.
# This enables a user to install this project without manually installing git or Python
cd "$(dirname "${BASH_SOURCE[0]}")"
echo -e "\n***** Installing InvokeAI... *****\n"
echo "Installing InvokeAI.."
echo ""
OS_NAME=$(uname -s)
case "${OS_NAME}" in
Linux*) OS_NAME="linux";;
Darwin*) OS_NAME="mac";;
*) echo "Unknown OS: $OS_NAME! This script runs only on Linux or Mac" && exit
Darwin*) OS_NAME="darwin";;
*) echo -e "\n----- Unknown OS: $OS_NAME! This script runs only on Linux or MacOS -----\n" && exit
esac
OS_ARCH=$(uname -m)
case "${OS_ARCH}" in
x86_64*) OS_ARCH="64";;
arm64*) OS_ARCH="arm64";;
*) echo "Unknown system architecture: $OS_ARCH! This script runs only on x86_64 or arm64" && exit
x86_64*) ;;
arm64*) ;;
*) echo -e "\n----- Unknown system architecture: $OS_ARCH! This script runs only on x86_64 or arm64 -----\n" && exit
esac
# https://mamba.readthedocs.io/en/latest/installation.html
if [ "$OS_NAME" == "linux" ] && [ "$OS_ARCH" == "arm64" ]; then OS_ARCH="aarch64"; fi
MAMBA_OS_NAME=$OS_NAME
MAMBA_ARCH=$OS_ARCH
if [ "$OS_NAME" == "darwin" ]; then
MAMBA_OS_NAME="osx"
fi
if [ "$OS_ARCH" == "linux" ]; then
MAMBA_ARCH="aarch64"
fi
if [ "$OS_ARCH" == "x86_64" ]; then
MAMBA_ARCH="64"
fi
PY_ARCH=$OS_ARCH
if [ "$OS_ARCH" == "arm64" ]; then
PY_ARCH="aarch64"
fi
# Compute device ('cd' segment of reqs files) detect goes here
# This needs a ton of work
# Suggestions:
# - lspci
# - check $PATH for nvidia-smi, gtt CUDA/GPU version from output
# - Surely there's a similar utility for AMD?
CD="cuda"
if [ "$OS_NAME" == "darwin" ] && [ "$OS_ARCH" == "arm64" ]; then
CD="mps"
fi
# config
export MAMBA_ROOT_PREFIX="$(pwd)/installer_files/mamba"
INSTALL_ENV_DIR="$(pwd)/installer_files/env"
MICROMAMBA_DOWNLOAD_URL="https://micro.mamba.pm/api/micromamba/${OS_NAME}-${OS_ARCH}/latest"
REPO_URL="https://github.com/invoke-ai/InvokeAI.git"
umamba_exists="F"
# figure out whether git and conda needs to be installed
if [ -e "$INSTALL_ENV_DIR" ]; then export PATH="$INSTALL_ENV_DIR/bin:$PATH"; fi
MICROMAMBA_DOWNLOAD_URL="https://micro.mamba.pm/api/micromamba/${MAMBA_OS_NAME}-${MAMBA_ARCH}/latest"
RELEASE_URL=https://github.com/invoke-ai/InvokeAI
RELEASE_SOURCEBALL=/archive/refs/heads/v2.1.3.tar.gz
PYTHON_BUILD_STANDALONE_URL=https://github.com/indygreg/python-build-standalone/releases/download
if [ "$OS_NAME" == "darwin" ]; then
PYTHON_BUILD_STANDALONE=20221002/cpython-3.10.7+20221002-${PY_ARCH}-apple-darwin-install_only.tar.gz
elif [ "$OS_NAME" == "linux" ]; then
PYTHON_BUILD_STANDALONE=20221002/cpython-3.10.7+20221002-${PY_ARCH}-unknown-linux-gnu-install_only.tar.gz
fi
PACKAGES_TO_INSTALL=""
if ! hash "conda" &>/dev/null; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL conda"; fi
if ! hash "git" &>/dev/null; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL git"; fi
if "$MAMBA_ROOT_PREFIX/micromamba" --version &>/dev/null; then umamba_exists="T"; fi
# (if necessary) install git and conda into a contained environment
if [ "$PACKAGES_TO_INSTALL" != "" ]; then
# download micromamba
if [ "$umamba_exists" == "F" ]; then
echo "Downloading micromamba from $MICROMAMBA_DOWNLOAD_URL to $MAMBA_ROOT_PREFIX/micromamba"
echo -e "\n***** Downloading micromamba from $MICROMAMBA_DOWNLOAD_URL to micromamba *****\n"
mkdir -p "$MAMBA_ROOT_PREFIX"
curl -L "$MICROMAMBA_DOWNLOAD_URL" | tar -xvj bin/micromamba -O > "$MAMBA_ROOT_PREFIX/micromamba"
curl -L "$MICROMAMBA_DOWNLOAD_URL" | tar -xvj bin/micromamba -O > micromamba
chmod u+x "$MAMBA_ROOT_PREFIX/micromamba"
chmod u+x "micromamba"
# test the mamba binary
echo "Micromamba version:"
"$MAMBA_ROOT_PREFIX/micromamba" --version
fi
# test the mamba binary
echo -e "\n***** Micromamba version: *****\n"
"micromamba" --version
# create the installer env
if [ ! -e "$INSTALL_ENV_DIR" ]; then
"$MAMBA_ROOT_PREFIX/micromamba" create -y --prefix "$INSTALL_ENV_DIR"
"micromamba" create -y --prefix "$INSTALL_ENV_DIR"
fi
echo "Packages to install:$PACKAGES_TO_INSTALL"
echo -e "\n***** Packages to install:$PACKAGES_TO_INSTALL *****\n"
"$MAMBA_ROOT_PREFIX/micromamba" install -y --prefix "$INSTALL_ENV_DIR" -c conda-forge $PACKAGES_TO_INSTALL
"micromamba" install -y --prefix "$INSTALL_ENV_DIR" -c conda-forge $PACKAGES_TO_INSTALL
if [ ! -e "$INSTALL_ENV_DIR" ]; then
echo "There was a problem while initializing micromamba. Cannot continue."
echo -e "\n----- There was a problem while initializing micromamba. Cannot continue. -----\n"
exit
fi
fi
if [ -e "$INSTALL_ENV_DIR" ]; then export PATH="$INSTALL_ENV_DIR/bin:$PATH"; fi
rm -f micromamba.exe
# get the repo (and load into the current directory)
if [ ! -e ".git" ]; then
git config --global init.defaultBranch main
git init
git remote add origin "$REPO_URL"
git fetch
git checkout origin/release-candidate-2-1 -ft
fi
export PATH="$INSTALL_ENV_DIR/bin:$PATH"
# create the environment
CONDA_BASEPATH=$(conda info --base)
source "$CONDA_BASEPATH/etc/profile.d/conda.sh" # otherwise conda complains about 'shell not initialized' (needed when running in a script)
# Download/unpack/clean up InvokeAI release sourceball
_err_msg="\n----- InvokeAI source download failed -----\n"
curl -L $RELEASE_URL/$RELEASE_SOURCEBALL --output InvokeAI.tgz
_err_exit $? _err_msg
_err_msg="\n----- InvokeAI source unpack failed -----\n"
tar -zxf InvokeAI.tgz
_err_exit $? _err_msg
conda activate
rm -f InvokeAI.tgz
if [ "$OS_NAME" == "mac" ]; then
PIP_EXISTS_ACTION=w CONDA_SUBDIR=osx-${OS_ARCH} conda env create -f environment-mac.yml
else
conda env remove -n invokeai
conda env create -f environment.yml
fi
_err_msg="\n----- InvokeAI source copy failed -----\n"
cd InvokeAI-*
cp -r . ..
_err_exit $? _err_msg
cd ..
status=$?
# cleanup
rm -rf InvokeAI-*/
rm -rf .dev_scripts/ .github/ docker-build/ tests/ requirements.in requirements-mkdocs.txt shell.nix
if test $status -ne 0
then
echo "Something went wrong while installing Python libraries and cannot continue."
echo "Please visit https://invoke-ai.github.io/InvokeAI/#installation for alternative"
echo "installation methods"
else
conda activate invokeai
# preload the models
echo "Calling the preload_models.py script"
python scripts/preload_models.py
status=$?
if test $status -ne 0
then
echo "The preload_models.py script crashed or was cancelled."
echo "InvokeAI is not ready to run. Try again by running"
echo "update.sh in this directory."
else
# tell the user their next steps
echo "You can now start generating images by running invoke.sh (inside this folder), using ./invoke.sh"
fi
fi
echo -e "\n***** Unpacked InvokeAI source *****\n"
conda activate invokeai
# Download/unpack/clean up python-build-standalone
_err_msg="\n----- Python download failed -----\n"
curl -L $PYTHON_BUILD_STANDALONE_URL/$PYTHON_BUILD_STANDALONE --output python.tgz
_err_exit $? _err_msg
_err_msg="\n----- Python unpack failed -----\n"
tar -zxf python.tgz
_err_exit $? _err_msg
rm -f python.tgz
echo -e "\n***** Unpacked python-build-standalone *****\n"
# create venv
_err_msg="\n----- problem creating venv -----\n"
./python/bin/python3 -E -s -m venv .venv
_err_exit $? _err_msg
# In reality, the following is ALL that 'activate.bat' does,
# aside from setting the prompt, which we don't care about
export PYTHONPATH=
export PATH=.venv/bin:$PATH
echo -e "\n***** Created Python virtual environment *****\n"
# Print venv's Python version
_err_msg="\n----- problem calling venv's python -----\n"
echo -e "We're running under"
.venv/bin/python3 --version
_err_exit $? _err_msg
_err_msg="\n----- pip update failed -----\n"
.venv/bin/python3 -m pip install --no-cache-dir --no-warn-script-location --upgrade pip
_err_exit $? _err_msg
echo -e "\n***** Updated pip *****\n"
_err_msg="\n----- requirements file copy failed -----\n"
cp installer/py3.10-${OS_NAME}-"${OS_ARCH}"-${CD}-reqs.txt requirements.txt
_err_exit $? _err_msg
_err_msg="\n----- main pip install failed -----\n"
.venv/bin/python3 -m pip install --no-cache-dir --no-warn-script-location -r requirements.txt
_err_exit $? _err_msg
_err_msg="\n----- clipseg install failed -----\n"
.venv/bin/python3 -m pip install --no-cache-dir --no-warn-script-location git+https://github.com/invoke-ai/clipseg.git@relaxed-python-requirement#egg=clipseg
_err_exit $? _err_msg
_err_msg="\n----- InvokeAI setup failed -----\n"
.venv/bin/python3 -m pip install --no-cache-dir --no-warn-script-location -e .
_err_exit $? _err_msg
echo -e "\n***** Installed Python dependencies *****\n"
# preload the models
.venv/bin/python3 scripts/preload_models.py
_err_msg="\n----- model download clone failed -----\n"
_err_exit $? _err_msg
echo -e "\n***** Finished downloading models *****\n"
echo -e "\n***** Installing invoke.sh ******\n"
cp installer/invoke.sh .
# more cleanup
rm -rf installer/ installer_files/
echo "All done! Run the command './invoke.sh' to start InvokeAI."
read -p "Press any key to exit..."
exit

27
installer/invoke.bat Normal file
View File

@ -0,0 +1,27 @@
@echo off
set PATH=c:\windows\system32
set PATH=.venv\Scripts;%PATH%
echo Do you want to generate images using the
echo 1. command-line
echo 2. browser-based UI
echo 3. open the developer console
set /P restore="Please enter 1, 2 or 3: "
IF /I "%restore%" == "1" (
echo Starting the InvokeAI command-line..
.venv\Scripts\python scripts\invoke.py
) ELSE IF /I "%restore%" == "2" (
echo Starting the InvokeAI browser-based UI..
.venv\Scripts\python scripts\invoke.py --web
) ELSE IF /I "%restore%" == "3" (
echo Developer Console
call where python
call python --version
cmd /k
) ELSE (
echo Invalid selection
pause
exit /b
)

24
installer/invoke.sh Executable file
View File

@ -0,0 +1,24 @@
#!/usr/bin/env bash
set -euo pipefail
IFS=$'\n\t'
PATH=.venv/scripts:$PATH
if [ "$0" != "bash" ]; then
echo "Do you want to generate images using the"
echo "1. command-line"
echo "2. browser-based UI"
echo "3. open the developer console"
read -p "Please enter 1, 2, or 3: " yn
case $yn in
1 ) printf "\nStarting the InvokeAI command-line..\n"; .venv/bin/python scripts/invoke.py;;
2 ) printf "\nStarting the InvokeAI browser-based UI..\n"; .venv/bin/python scripts/invoke.py --web;;
3 ) printf "\nDeveloper Console:\n"; file_name=$(basename "${BASH_SOURCE[0]}"); bash --init-file "$file_name";;
* ) echo "Invalid selection"; exit;;
esac
else # in developer console
python --version
echo "Press ^D to exit"
export PS1="(InvokeAI) \u@\h \w> "
fi

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@ -3,9 +3,15 @@ InvokeAI
Project homepage: https://github.com/invoke-ai/InvokeAI
Installation on Windows:
Please double-click the 'install.bat' file (while keeping it inside the invokeAI folder).
NOTE: You might need to enable Windows Long Paths. If you're not sure,
then you almost certainly need to. Simply double-click the 'WinLongPathsEnabled.reg'
file. Note that you will need to have admin privileges in order to
do this.
Please double-click the 'install.bat' file (while keeping it inside the invokeAI folder).
Installation on Linux and Mac:
Please open the terminal, and run './install.sh' (while keeping it inside the invokeAI folder).
Please open the terminal, and run './install.sh' (while keeping it inside the invokeAI folder).
After installation, please run the 'invoke.bat' file (on Windows) or 'invoke.sh' file (on Linux/Mac) to start InvokeAI.
After installation, please run the 'invoke.bat' file (on Windows) or 'invoke.sh'
file (on Linux/Mac) to start InvokeAI.

24
installer/requirements.in Normal file
View File

@ -0,0 +1,24 @@
--prefer-binary
--extra-index-url https://download.pytorch.org/whl/cu116
--trusted-host https://download.pytorch.org
albumentations
diffusers
eventlet
flask_cors
flask_socketio
flaskwebgui
getpass_asterisk
imageio-ffmpeg
pyreadline3
realesrgan
send2trash
streamlit
taming-transformers-rom1504
test-tube
torch-fidelity
torchvision==0.13.1 ; platform_system == 'Darwin'
torchvision==0.13.1+cu116 ; platform_system == 'Linux' or platform_system == 'Windows'
transformers
https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip
https://github.com/TencentARC/GFPGAN/archive/2eac2033893ca7f427f4035d80fe95b92649ac56.zip
https://github.com/invoke-ai/k-diffusion/archive/7f16b2c33411f26b3eae78d10648d625cb0c1095.zip

View File

@ -567,9 +567,8 @@ class Generate:
seed = opt.seed or args.seed
if seed is None or seed < 0:
seed = random.randrange(0, np.iinfo(np.uint32).max)
prompt = opt.prompt or args.prompt or ''
print(f'>> using seed {seed} and prompt "{prompt}" for {image_path}')
# try to reuse the same filename prefix as the original file.

View File

@ -47,7 +47,6 @@ def get_uc_and_c_and_ec(prompt_string_uncleaned, model, log_tokens=False, skip_n
parsed_prompt = pp.parse_conjunction(prompt_string_cleaned).prompts[0]
parsed_negative_prompt: FlattenedPrompt = pp.parse_conjunction(unconditioned_words).prompts[0]
print(f">> Parsed prompt to {parsed_prompt}")
conditioning = None
cac_args:CrossAttentionControl.Arguments = None

View File

@ -169,7 +169,8 @@ class Inpaint(Img2Img):
# Fill missing areas of original image
init_filled = self.tile_fill_missing(
self.pil_image.copy(),
seed = self.seed if self.seed >= 0 else self.new_seed(),
seed = self.seed if (self.seed is not None
and self.seed >= 0) else self.new_seed(),
tile_size = tile_size
)
init_filled.paste(init_image, (0,0), init_image.split()[-1])

View File

@ -72,6 +72,7 @@ class GFPGAN():
image = image.resize(res.size)
res = Image.blend(image, res, strength)
if torch.cuda.is_available():
torch.cuda.empty_cache()
self.gfpgan = None

View File

@ -35,8 +35,8 @@ from PIL import Image, ImageOps
from torchvision import transforms
CLIP_VERSION = 'ViT-B/16'
CLIPSEG_WEIGHTS = 'src/clipseg/weights/rd64-uni.pth'
CLIPSEG_WEIGHTS_REFINED = 'src/clipseg/weights/rd64-uni-refined.pth'
CLIPSEG_WEIGHTS = 'models/clipseg/clipseg_weights/rd64-uni.pth'
CLIPSEG_WEIGHTS_REFINED = 'models/clipseg/clipseg_weights/rd64-uni-refined.pth'
CLIPSEG_SIZE = 352
class SegmentedGrayscale(object):

View File

@ -1,3 +0,0 @@
[tool.blue]
line-length = 90
target-version = ['py310']

View File

@ -1,27 +0,0 @@
albumentations==0.4.3
einops==0.3.0
diffusers==0.6.0
huggingface-hub==0.8.1
imageio==2.9.0
imageio-ffmpeg==0.4.2
kornia==0.6.0
numpy==1.23.1
--pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cpu
omegaconf==2.1.1
opencv-python==4.6.0.66
pillow==9.2.0
pudb==2019.2
torch==1.12.1
torchvision==0.13.0
pytorch-lightning==1.7.7
streamlit==1.12.0
test-tube>=0.7.5
torch-fidelity==0.3.0
torchmetrics==0.6.0
transformers==4.21.3
-e git+https://github.com/openai/CLIP.git@main#egg=clip
-e git+https://github.com/CompVis/taming-transformers.git@master#egg=taming-transformers
-e git+https://github.com/lstein/k-diffusion.git@master#egg=k-diffusion
-e git+https://github.com/TencentARC/GFPGAN.git#egg=gfpgan
-e git+https://github.com/invoke-ai/clipseg.git@models-rename#egg=clipseg
-e .

View File

@ -613,6 +613,7 @@ def do_textmask(gen, opt, callback):
image_path = os.path.join(opt.outdir,image_path)
assert os.path.exists(image_path), '** "{opt.prompt}" not found. Please enter the name of an existing image file to mask **'
assert opt.text_mask is not None and len(opt.text_mask) >= 1, '** Please provide a text mask with -tm **'
opt.input_file_path = image_path
tm = opt.text_mask[0]
threshold = float(opt.text_mask[1]) if len(opt.text_mask) > 1 else 0.5
gen.apply_textmask(
@ -633,6 +634,7 @@ def do_postprocess (gen, opt, callback):
file_path = os.path.join(opt.outdir,file_path)
opt.input_file_path = file_path
tool=None
if opt.facetool_strength > 0:
tool = opt.facetool

View File

@ -104,13 +104,15 @@ def postscript():
print(
'''\n** Model Installation Successful **\nYou're all set! You may now launch InvokeAI using one of these two commands:
Web version:
python scripts/invoke.py --web (connect to http://localhost:9090)
Command-line version:
python scripts/invoke.py
Remember to activate that 'invokeai' environment before running invoke.py.
Or, if you used one of the automated installers, execute "invoke.sh" (Linux/Mac)
or "invoke.bat" (Windows) to start the script.
Have fun!
'''
)
@ -415,7 +417,7 @@ def download_kornia():
#---------------------------------------------
def download_clip():
print('Loading CLIP model...',end='')
print('Loading CLIP model (ignore deprecation errors)...',end='')
sys.stdout.flush()
version = 'openai/clip-vit-large-patch14'
tokenizer = CLIPTokenizer.from_pretrained(version)
@ -424,7 +426,7 @@ def download_clip():
#---------------------------------------------
def download_gfpgan():
print('Installing models from RealESRGAN and facexlib...',end='')
print('Installing models from RealESRGAN and facexlib (ignore deprecation errors)...',end='')
try:
from realesrgan import RealESRGANer
from realesrgan.archs.srvgg_arch import SRVGGNetCompact
@ -442,7 +444,7 @@ def download_gfpgan():
print('Error loading ESRGAN:')
print(traceback.format_exc())
print('Loading models from GFPGAN')
print('Loading models from GFPGAN...',end='')
for model in (
[
'https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth',
@ -489,22 +491,23 @@ def download_clipseg():
import zipfile
try:
model_url = 'https://owncloud.gwdg.de/index.php/s/ioHbRzFx6th32hn/download'
model_dest = 'src/clipseg/clipseg_weights.zip'
weights_dir = 'src/clipseg/weights'
if not os.path.exists(weights_dir):
model_dest = 'models/clipseg/clipseg_weights'
weights_zip = 'models/clipseg/weights.zip'
if not os.path.exists(model_dest):
os.makedirs(os.path.dirname(model_dest), exist_ok=True)
if not os.path.exists('src/clipseg/weights/rd64-uni-refined.pth'):
request.urlretrieve(model_url,model_dest)
with zipfile.ZipFile(model_dest,'r') as zip:
zip.extractall('src/clipseg')
os.rename('src/clipseg/clipseg_weights','src/clipseg/weights')
os.remove(model_dest)
from clipseg_models.clipseg import CLIPDensePredT
if not os.path.exists(f'{model_dest}/rd64-uni-refined.pth'):
request.urlretrieve(model_url,weights_zip)
with zipfile.ZipFile(weights_zip,'r') as zip:
zip.extractall('models/clipseg')
os.remove(weights_zip)
from clipseg.clipseg import CLIPDensePredT
model = CLIPDensePredT(version='ViT-B/16', reduce_dim=64, )
model.eval()
model.load_state_dict(
torch.load(
'src/clipseg/weights/rd64-uni-refined.pth',
'models/clipseg/clipseg_weights/rd64-uni-refined.pth',
map_location=torch.device('cpu')
),
strict=False,

View File

@ -3,7 +3,7 @@ from setuptools import setup, find_packages
setup(
name='invoke-ai',
version='2.1.3',
description='',
description='InvokeAI text to image generation toolkit',
packages=find_packages(),
install_requires=[
'torch',
@ -11,3 +11,4 @@ setup(
'tqdm',
],
)

View File

@ -0,0 +1,23 @@
#!/bin/bash
cd "$(dirname "${BASH_SOURCE[0]}")"
# make the installer zip for linux and mac
rm -rf invokeAI
mkdir -p invokeAI
cp install.sh invokeAI
cp readme.txt invokeAI
zip -r invokeAI-src-installer-linux.zip invokeAI
zip -r invokeAI-src-installer-mac.zip invokeAI
# make the installer zip for windows
rm -rf invokeAI
mkdir -p invokeAI
cp install.bat invokeAI
cp readme.txt invokeAI
cp WinLongPathsEnabled.reg invokeAI
zip -r invokeAI-src-installer-windows.zip invokeAI
echo "The installer zips are ready to be distributed.."

View File

@ -0,0 +1,118 @@
@echo off
@rem This script will install git and conda (if not found on the PATH variable)
@rem using micromamba (an 8mb static-linked single-file binary, conda replacement).
@rem For users who already have git and conda, this step will be skipped.
@rem Next, it'll checkout the project's git repo, if necessary.
@rem Finally, it'll create the conda environment and preload the models.
@rem This enables a user to install this project without manually installing conda and git.
echo "Installing InvokeAI.."
echo.
@rem config
set MAMBA_ROOT_PREFIX=%cd%\installer_files\mamba
set INSTALL_ENV_DIR=%cd%\installer_files\env
set MICROMAMBA_DOWNLOAD_URL=https://github.com/cmdr2/stable-diffusion-ui/releases/download/v1.1/micromamba.exe
set REPO_URL=https://github.com/invoke-ai/InvokeAI.git
set umamba_exists=F
@rem Change the download URL to an InvokeAI repo's release URL
@rem figure out whether git and conda needs to be installed
if exist "%INSTALL_ENV_DIR%" set PATH=%INSTALL_ENV_DIR%;%INSTALL_ENV_DIR%\Library\bin;%INSTALL_ENV_DIR%\Scripts;%INSTALL_ENV_DIR%\Library\usr\bin;%PATH%
set PACKAGES_TO_INSTALL=
call conda --version >.tmp1 2>.tmp2
if "%ERRORLEVEL%" NEQ "0" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% conda
call git --version >.tmp1 2>.tmp2
if "%ERRORLEVEL%" NEQ "0" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% git
call "%MAMBA_ROOT_PREFIX%\micromamba.exe" --version >.tmp1 2>.tmp2
if "%ERRORLEVEL%" EQU "0" set umamba_exists=T
@rem (if necessary) install git and conda into a contained environment
if "%PACKAGES_TO_INSTALL%" NEQ "" (
@rem download micromamba
if "%umamba_exists%" == "F" (
echo "Downloading micromamba from %MICROMAMBA_DOWNLOAD_URL% to %MAMBA_ROOT_PREFIX%\micromamba.exe"
mkdir "%MAMBA_ROOT_PREFIX%"
call curl -L "%MICROMAMBA_DOWNLOAD_URL%" > "%MAMBA_ROOT_PREFIX%\micromamba.exe"
@rem test the mamba binary
echo Micromamba version:
call "%MAMBA_ROOT_PREFIX%\micromamba.exe" --version
)
@rem create the installer env
if not exist "%INSTALL_ENV_DIR%" (
call "%MAMBA_ROOT_PREFIX%\micromamba.exe" create -y --prefix "%INSTALL_ENV_DIR%"
)
echo "Packages to install:%PACKAGES_TO_INSTALL%"
call "%MAMBA_ROOT_PREFIX%\micromamba.exe" install -y --prefix "%INSTALL_ENV_DIR%" -c conda-forge %PACKAGES_TO_INSTALL%
if not exist "%INSTALL_ENV_DIR%" (
echo "There was a problem while installing%PACKAGES_TO_INSTALL% using micromamba. Cannot continue."
pause
exit /b
)
)
set PATH=%INSTALL_ENV_DIR%;%INSTALL_ENV_DIR%\Library\bin;%INSTALL_ENV_DIR%\Scripts;%INSTALL_ENV_DIR%\Library\usr\bin;%PATH%
@rem get the repo (and load into the current directory)
if not exist ".git" (
call git init
call git config --local init.defaultBranch main
call git remote add origin %REPO_URL%
call git fetch
call git checkout origin/main -ft
)
@rem activate the base env
call conda activate
@rem create the environment
call conda env remove -n invokeai
copy environments-and-requirements\environment-win-cuda.yml environment.yml
call conda env create
if "%ERRORLEVEL%" NEQ "0" (
echo ""
echo "Something went wrong while installing Python libraries and cannot continue.
echo "Please visit https://invoke-ai.github.io/InvokeAI/#installation for alternative"
echo "installation methods."
echo "Press any key to continue"
pause
exit /b
)
copy source_installer\invoke.bat invoke.bat
copy source_installer\update.bat update.bat
call conda activate invokeai
@rem preload the models
call python scripts\preload_models.py
if "%ERRORLEVEL%" NEQ "0" (
echo ""
echo "The preload_models.py script crashed or was cancelled."
echo "InvokeAI is not ready to run. To run preload_models.py again,"
echo "run the command 'update.bat' in this directory."
echo "Press any key to continue"
pause
exit /b
)
@rem tell the user their next steps
echo ""
echo "* InvokeAI installed successfully *"
echo "You can now start generating images by double-clicking the 'invoke.bat' file (inside this folder)
echo "Press any key to continue"
pause
exit 0

138
source_installer/install.sh Executable file
View File

@ -0,0 +1,138 @@
#!/bin/bash
# This script will install git and conda (if not found on the PATH variable)
# using micromamba (an 8mb static-linked single-file binary, conda replacement).
# For users who already have git and conda, this step will be skipped.
# Next, it'll checkout the project's git repo, if necessary.
# Finally, it'll create the conda environment and preload the models.
# This enables a user to install this project without manually installing conda and git.
cd "$(dirname "${BASH_SOURCE[0]}")"
echo "Installing InvokeAI.."
echo ""
OS_NAME=$(uname -s)
case "${OS_NAME}" in
Linux*) OS_NAME="linux";;
Darwin*) OS_NAME="mac";;
*) echo "Unknown OS: $OS_NAME! This script runs only on Linux or Mac" && exit
esac
OS_ARCH=$(uname -m)
case "${OS_ARCH}" in
x86_64*) OS_ARCH="64";;
arm64*) OS_ARCH="arm64";;
*) echo "Unknown system architecture: $OS_ARCH! This script runs only on x86_64 or arm64" && exit
esac
# https://mamba.readthedocs.io/en/latest/installation.html
if [ "$OS_NAME" == "linux" ] && [ "$OS_ARCH" == "arm64" ]; then OS_ARCH="aarch64"; fi
# config
export MAMBA_ROOT_PREFIX="$(pwd)/installer_files/mamba"
INSTALL_ENV_DIR="$(pwd)/installer_files/env"
MICROMAMBA_DOWNLOAD_URL="https://micro.mamba.pm/api/micromamba/${OS_NAME}-${OS_ARCH}/latest"
REPO_URL="https://github.com/invoke-ai/InvokeAI.git"
umamba_exists="F"
# figure out whether git and conda needs to be installed
if [ -e "$INSTALL_ENV_DIR" ]; then export PATH="$INSTALL_ENV_DIR/bin:$PATH"; fi
PACKAGES_TO_INSTALL=""
if ! $(which conda) -V &>/dev/null; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL conda"; fi
if ! which git &>/dev/null; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL git"; fi
if "$MAMBA_ROOT_PREFIX/micromamba" --version &>/dev/null; then umamba_exists="T"; fi
# (if necessary) install git and conda into a contained environment
if [ "$PACKAGES_TO_INSTALL" != "" ]; then
# download micromamba
if [ "$umamba_exists" == "F" ]; then
echo "Downloading micromamba from $MICROMAMBA_DOWNLOAD_URL to $MAMBA_ROOT_PREFIX/micromamba"
mkdir -p "$MAMBA_ROOT_PREFIX"
curl -L "$MICROMAMBA_DOWNLOAD_URL" | tar -xvj bin/micromamba -O > "$MAMBA_ROOT_PREFIX/micromamba"
chmod u+x "$MAMBA_ROOT_PREFIX/micromamba"
# test the mamba binary
echo "Micromamba version:"
"$MAMBA_ROOT_PREFIX/micromamba" --version
fi
# create the installer env
if [ ! -e "$INSTALL_ENV_DIR" ]; then
"$MAMBA_ROOT_PREFIX/micromamba" create -y --prefix "$INSTALL_ENV_DIR"
fi
echo "Packages to install:$PACKAGES_TO_INSTALL"
"$MAMBA_ROOT_PREFIX/micromamba" install -y --prefix "$INSTALL_ENV_DIR" -c conda-forge $PACKAGES_TO_INSTALL
if [ ! -e "$INSTALL_ENV_DIR" ]; then
echo "There was a problem while initializing micromamba. Cannot continue."
exit
fi
fi
if [ -e "$INSTALL_ENV_DIR" ]; then export PATH="$INSTALL_ENV_DIR/bin:$PATH"; fi
# get the repo (and load into the current directory)
if [ ! -e ".git" ]; then
git init
git config --local init.defaultBranch main
git remote add origin "$REPO_URL"
git fetch
git checkout origin/main -ft
fi
# create the environment
CONDA_BASEPATH=$(conda info --base)
source "$CONDA_BASEPATH/etc/profile.d/conda.sh" # otherwise conda complains about 'shell not initialized' (needed when running in a script)
conda activate
if [ "$OS_NAME" == "mac" ]; then
echo "Macintosh system detected. Installing MPS and CPU support."
ln -sf environments-and-requirements/environment-mac.yml environment.yml
else
if (lsmod | grep amdgpu) &>/dev/null ; then
echo "Linux system with AMD GPU driver detected. Installing ROCm and CPU support"
ln -sf environments-and-requirements/environment-lin-amd.yml environment.yml
else
echo "Linux system detected. Installing CUDA and CPU support."
ln -sf environments-and-requirements/environment-lin-cuda.yml environment.yml
fi
fi
conda env update
status=$?
if test $status -ne 0
then
echo "Something went wrong while installing Python libraries and cannot continue."
echo "Please visit https://invoke-ai.github.io/InvokeAI/#installation for alternative"
echo "installation methods"
else
ln -sf ./source_installer/invoke.sh .
ln -sf ./source_installer/update.sh .
conda activate invokeai
# preload the models
echo "Calling the preload_models.py script"
python scripts/preload_models.py
status=$?
if test $status -ne 0
then
echo "The preload_models.py script crashed or was cancelled."
echo "InvokeAI is not ready to run. Try again by running"
echo "update.sh in this directory."
else
# tell the user their next steps
echo "You can now start generating images by running invoke.sh (inside this folder), using ./invoke.sh"
fi
fi
conda activate invokeai

View File

@ -23,6 +23,7 @@ if [ "$0" != "bash" ]; then
* ) echo "Invalid selection"; exit;;
esac
else # in developer console
which python
python --version
echo "Press ^D to exit"
export PS1="(InvokeAI) \u@\h \w> "
fi

View File

@ -0,0 +1,16 @@
InvokeAI
Project homepage: https://github.com/invoke-ai/InvokeAI
Installation on Windows:
You may need to enable Windows Long Paths to install InvokeAI. If you're not
sure what this is, you almost certainly need to do this. Simply double-click the
"WinLongPathsEnabled.reg" file located in this directory, and approve the Windows
warnings. Note that you will need to have admin privileges in order to do this.
Then double-click the 'install.bat' file (while keeping it inside the invokeAI folder).
Installation on Linux and Mac:
Please open the terminal, and run './install.sh' (while keeping it inside the invokeAI folder).
After installation, please run the 'invoke.bat' file (on Windows) or 'invoke.sh' file (on Linux/Mac) to start InvokeAI.

View File

@ -22,3 +22,5 @@ case "${OS_NAME}" in
esac
python scripts/preload_models.py